mzhengrpi / rpifield

RPIfield dataset for Person Re-identification

RPIfield

RPIfield dataset is a new multi-camera multi-shot re-id dataset collected at Rensselaer Polytechnic Institute, USA. Timestamps of each person image is preserved. To automatically collect person images, we used an off-the-shelf person detector, based on the aggregated channel features (ACF) algorithm. The statistics of the proposed RPIfield dataset are provided below:

• 12 synchronized outdoor cameras
• 112 known participants, with each showing up in at least 3 camera views
• ~4000 distractors
• 30 hours of video length in total,

Cam	# bboxes	# participants	# reapp	# distractors	#Sequences
1	59,230	78	107	297	485
2	112,523	83	94	653	830
3	72,005	74	68	822	964
4	53,986	70	72	393	536
5	67,672	63	52	781	896
6	56,472	64	38	865	967
7	17,809	48	36	93	177
8	36,338	55	40	266	361
9	3,910	40	16	32	88
10	10,492	62	51	105	218
11	73,601	76	149	448	673
12	37,543	70	79	233	382

More details can be found in this paper

How to access

1. Download the dataset from [Google Drive] (https://drive.google.com/file/d/1GO1zm7vCAJwXgJtoFyUs367_Knz8Ev0A/view?usp=sharing) or [Baidu Disk] (https://pan.baidu.com/s/1TsPRkRQwI_i88zPQqGC3oQ) (Extract Code：RPIf) and extract the files.
2. There are 4 items inside the package.

• "Data". This folder has 12 subfolders (Cam_1 to Cam_12) for 12 camera views. In each folder "Cam_", we include image sequence(s) for each identity at different times in different subfolder(s) with name as the label of the identity. Label 1-112 indicate the known actors, Label #>= 10000 corresponds to pedestrians (distractors). Note: appearance(s) of each participant at different time are put in different subfolders, e.g., subfolder "2_1" contains the first reappearance (image sequence) of person 2, subfolder "3_2" includes the second reappearance of person 3. For the naming rule of each image, e.g., "Cam_1f_44841.png", "Cam_1": camera 1, "f_44841": frame number = 44841.

• "Data_Info". This folder has 12 items corresponds to the collective info for data in "Data" folder. "Cam_.mat" collects image name info, id info and timestamp info for data in each camera view.

• "load_data.m" file. You are able to access the image data from "Struct" variable by simply running this script. Field "Struct.Imgnames", "Struct.PersonId", "Struct.CamID", "Struct.TimeStamp" and "Struct.ReappInd" are the image name, identity label, Camera label, timestamps, reappearance info for each image;

Specifically, you can access the original image by calling following Matlab command: imread(fullfile(strcat('.\Data\Cam_',num2str(Cam#)),Struct.Imgnames{Cam#}{Img#}));

References

Please kindly cite the paper if you use this dataset in your research. Enjoy!

@inproceedings{zheng2018rpifield, title={RPIField: A New Datasef for Temporally Evaluating Person Re-Identification}, author={Zheng, Meng and Karanam, Srikrishna and Radke, Richard J}, booktitle={IEEE Conference on Computer Vision and Pattern Recognition Workshops}, year={2018} }

@conference{Srik_ICDSC17, author = {S. Karanam and E. Lam and R. J. Radke}, title = {Rank Persistence: Assessing the Temporal Performance of Real-World Person Re-Identification.}, booktitle = {ICDSC}, year=2017 }

rpifield's Issues

What is the license for the RPIField dataset?

Hi, Can this be used for commercial purposes?